Detailed Application Testing of Tongyi Wanxiang Model 2.1 (Part 2)

Detailed Application Testing of Tongyi Wanxiang Model 2.1 (Part 2)

Continuing from the previous article, we continue testing the Tongyi Wanxiang 2.1 model for large-scale action presentation. [Test 5] Large-Scale Action Presentation Below is an introduction from the news media. Next, we will conduct similar tests to see the performance of the new model during large-scale motion scenes. We refer to the media’s prompts, using … Read more

How to Quickly Generate High-Quality Videos with Tongyi Wanxiang 2.1

How to Quickly Generate High-Quality Videos with Tongyi Wanxiang 2.1

▌Introduction by Guotou On January 9, 2025, at 17:40, the official WeChat account of Tongyi announced the upgrade of the Tongyi Wanxiang model to version 2.1, showcasing significant improvements in both video and image generation capabilities. Let’s take a look at the promotional video from the official Tongyi account. Guotou’s Test Results Based on the … Read more

Create Stunning Crystal Animal Videos in 2 Minutes!

Create Stunning Crystal Animal Videos in 2 Minutes!

Editor / A Di Layout / A Di This isA Di’s Official Account‘s108thoriginal article – Introduction – How to make transparent kittens and puppies? They are very beautiful and have received thousands of likes on a certain platform. Some friends have asked me this question. Today, I will teach everyone how to create crystal-clear small … Read more

Chronos: Slow Thinking RAG Technology for News Timeline Summarization

Chronos: Slow Thinking RAG Technology for News Timeline Summarization

Paper: https://arxiv.org/abs/2501.00888 Github: https://github.com/Alibaba-NLP/CHRONOS Demo: https://modelscope.cn/studios/vickywu1022/CHRONOS In the digital age, the exponential growth of news information makes it crucial to extract and organize historical event timelines from massive texts. To address this challenge, Alibaba’s Tongyi Lab and researchers from Shanghai Jiao Tong University proposed a new framework for news timeline summarization based on agents—CHRONOS, named … Read more

Overview of Agentic Retrieval-Augmented Generation

Overview of Agentic Retrieval-Augmented Generation

Large language models (LLMs) have revolutionized the field of artificial intelligence (AI) by enabling human-like text generation and natural language understanding. However, their reliance on static training data limits their responsiveness to dynamic real-time queries, resulting in outdated or inaccurate outputs. Retrieval-Augmented Generation (RAG) serves as a solution by integrating real-time data retrieval to enhance … Read more

Strategies to Enhance RAG System Performance

Strategies to Enhance RAG System Performance

The RAG (Retrieval-Augmented Generation) model, commonly referred to as the RAG system, is widely used in large model applications. The principle of the model is quite simple: it retrieves information from a dataset based on user needs and then uses a large model for reasoning and generation. The advantage of RAG lies in its ability … Read more

Comprehensive Overview of Agentic RAG

Comprehensive Overview of Agentic RAG

https://arxiv.org/pdf/2501.09136 Overview of Retrieval-Augmented Generation (RAG) Retrieval-Augmented Generation (RAG) represents a significant advancement in the field of artificial intelligence by combining the generative capabilities of Large Language Models (LLMs) with real-time data retrieval. While LLMs excel in natural language processing, their reliance on static pre-trained data often results in outdated or incomplete responses. RAG achieves … Read more

MedGPT: Demonstrating Excellent Medical Performance Based on RAG Evaluation Framework

MedGPT: Demonstrating Excellent Medical Performance Based on RAG Evaluation Framework

The Retrieval-Augmented Generation (RAG) technology is revolutionizing the AI application field by integrating external knowledge bases with internal knowledge of LLM (Large Language Model), enhancing the accuracy and reliability of AI systems. The knowledge “recall ability” of the multimodal knowledge extractor directly determines whether the large model can obtain accurate professional knowledge when answering reasoning … Read more